Energy leaders cite the same two primary barriers to adoption as 2025: Cybersecurity risks remain the leading barrier, named by 43% of leaders, down from 49%. Data quality and consistency is second at 39%. Lack of skilled talent holds third at 32%, now level with unpredictable AI usage costs, which have fallen from 37%. For a technology moving as quickly as AI, the consistency is telling. Leaders The industry's biggest AI challenges are the same as they were a year ago. As attention shifts toward agentic systems and greater autonomy, trusted data, robust security and clear governance remain the primary blockers to adoption. are not discovering new problems with AI in energy. They are living with the same issues and describing them more precisely than they did in 2025. What has changed is what else appears on the list. Geopolitical risk enters at 24%. Limited cross-border AI coordination at 18%. Supply-chain risk at 10%. None of these made the list for last year’s report. The challenges have widened from the ones a company can fix itself to the ones it cannot — and 77% say AI's potential in the energy sector is held back because the system is too fragmented and siloed to apply it at scale. You can make a strong argument that cybersecurity and data quality are different vectors for a single underlying condition, namely whether an organization can rely on what its data says, and control who is able to 3 CYBERSECURITY AND DATA READINESS REMAIN CHALLENGES FOR SCALE 20